The present disclosure relates generally to the field of computing system security, and more specifically, to enhanced authentication with dark web analytics.
Network-connected computing systems often require credentials to be provided and authenticated before granting access to computing services and information. For example, an end user of a computing device (e.g., mobile device, desktop, laptop, etc.) may provide user credentials to access an online financial services account or to facilitate an online transaction via the financial services account. User credentials can include, for example, a personal identification number (PIN), a user identifier, a password. Enhanced authentication techniques can provide greater security, but may impact the user experience. For example, multi-factor authentication can require an end user of a computing device to provide two or more authentication factors before gaining access to the services and information. Risk analytics may be employed by financial systems to evaluate transactions based on various risk factors and policies associated with a requested transaction (e.g., online payment, transfer, etc.) to determine whether to require additional authentication, deny the transaction, or allow the transaction.